During recent years, the vesicles of the endosomal/lysosomal (E/L) system have emerged as key sites for the regulation of many cellular functions. Their biological importance is exemplified by the occurrence of numerous lysosomal storage diseases (LSDs), each resulting from the deficiency of a single protein in the system, that manifest with severe phenotypes, usually leading to neurodegeneration and early death. How these single gene defects can produce such severe phenotypes is not entirely clear;dissection of the metabolic changes that occur within the E/L system should provide insights towards understanding disease pathogenesis and provide new avenues for screening, early diagnosis, and monitoring of therapeutic approaches. That disease pathogenesis of the LSDs originates in the E/L system presents unique challenges for the characterization of metabolic changes in patients, since circulating biological fluids do not offer a comprehensive view of these changes and obtaining tissue samples on a regular basis is not feasible. We will use a novel approach involving exosomes to identify and characterize the metabolic changes that occur in LSDs. Exosomes are uniquely suited for this type of study because they are secreted by many cell types and are found in biological fluids such as plasma, urine, and cerebrospinal fluid and are derived from the membranes of late endosomes. Thus, they contain a subset of proteins normally found there and can serve as useful source material to characterize the changes that occur within the E/L system as a result of disease. We hypothesize that exosomes derived from disease cells will reflect protein and lipid changes that are specific to the disease. In this respect, exosomes will provide a "fingerprint" or "barcode" unique to each LSD. Here, we propose to: 1) test the hypothesis that exosomes from human disease cells have unique protein and/or lipid identifiers that will distinguish them from those of normal cells and reveal alterations of specific metabolic pathways. We will map these pathways and validatelevaluate these changes in vitro and in vivo. 2) Test the prediction that changes in glucose metabolism correlate with NPC1 disease severity and can be used to monitor disease progression. In short, this new approach is a new paradigm in metabolic analysis and will facilitate the efficient discovery/characterization of altered LSD metabolic pathways and provide us with the next step in understanding lysosomal storage disease pathogenesis.